Proceedings of the International Conference on Image Processing (V 3), Singapore, 24-27 October 2004, 1775-1778

Abstract:

We propose a technique for super-resolution imaging of a scene from observations at different camera zooms. Given a sequence of images with different zoom factors of a static scene, we obtain a picture of the entire scene at a resolution corresponding to the most zoomed observation. We model the high resolution image as a simultaneous autoregressive (SAR) model, the parameters of which are learnt from the most zoomed observation. Assuming that the entire scene can be described by a homogeneous SAR model, the learnt parameters are then used in a suitable regularization technique to estimate the high resolution field.